Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations43778
Missing cells6
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 MiB
Average record size in memory104.0 B

Variable types

DateTime1
Numeric11

Alerts

DE_load_actual_entsoe_transparency is highly overall correlated with Price (EUR/MWhe)High correlation
DE_radiation_diffuse_horizontal is highly overall correlated with DE_radiation_direct_horizontal and 1 other fieldsHigh correlation
DE_radiation_direct_horizontal is highly overall correlated with DE_radiation_diffuse_horizontal and 2 other fieldsHigh correlation
DE_solar_capacity is highly overall correlated with DE_wind_capacity and 1 other fieldsHigh correlation
DE_solar_generation_actual is highly overall correlated with DE_radiation_diffuse_horizontal and 2 other fieldsHigh correlation
DE_temperature is highly overall correlated with DE_radiation_direct_horizontal and 1 other fieldsHigh correlation
DE_wind_capacity is highly overall correlated with DE_solar_capacity and 1 other fieldsHigh correlation
Oil_Price is highly overall correlated with DE_solar_capacity and 1 other fieldsHigh correlation
Price (EUR/MWhe) is highly overall correlated with DE_load_actual_entsoe_transparencyHigh correlation
cet_cest_timestamp has unique values Unique
DE_solar_generation_actual has 18985 (43.4%) zeros Zeros
DE_radiation_direct_horizontal has 18724 (42.8%) zeros Zeros
DE_radiation_diffuse_horizontal has 18724 (42.8%) zeros Zeros

Reproduction

Analysis started2025-04-21 14:29:10.913747
Analysis finished2025-04-21 14:29:44.929787
Duration34.02 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

cet_cest_timestamp
Date

Unique 

Distinct43778
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size684.0 KiB
Minimum2015-01-01 00:00:00+01:00
Maximum2019-12-30 01:00:00+01:00
Invalid dates25704
Invalid dates (%)58.7%
2025-04-21T17:29:45.393473image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:45.661581image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

DE_load_actual_entsoe_transparency
Real number (ℝ)

High correlation 

Distinct25332
Distinct (%)57.9%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean55867.097
Minimum31307
Maximum77549
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size684.0 KiB
2025-04-21T17:29:45.956799image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum31307
5-th percentile40239.8
Q147440
median55484
Q364796
95-th percentile70968.2
Maximum77549
Range46242
Interquartile range (IQR)17356

Descriptive statistics

Standard deviation10006.677
Coefficient of variation (CV)0.17911574
Kurtosis-1.1320954
Mean55867.097
Median Absolute Deviation (MAD)8680
Skewness-0.034148836
Sum2.4456939 × 109
Variance1.0013358 × 108
MonotonicityNot monotonic
2025-04-21T17:29:46.371484image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46724 8
 
< 0.1%
45129 8
 
< 0.1%
66809 7
 
< 0.1%
63092 7
 
< 0.1%
47964 7
 
< 0.1%
58055 7
 
< 0.1%
53534 7
 
< 0.1%
51016 7
 
< 0.1%
44841 7
 
< 0.1%
42851 7
 
< 0.1%
Other values (25322) 43705
99.8%
ValueCountFrequency (%)
31307 1
< 0.1%
31335 1
< 0.1%
31598 1
< 0.1%
31772 1
< 0.1%
32418 1
< 0.1%
32617 1
< 0.1%
32625 1
< 0.1%
32636 1
< 0.1%
32824 1
< 0.1%
32889 1
< 0.1%
ValueCountFrequency (%)
77549 1
< 0.1%
76925 1
< 0.1%
76904 1
< 0.1%
76871 1
< 0.1%
76783 1
< 0.1%
76602 1
< 0.1%
76574 1
< 0.1%
76552 1
< 0.1%
76551 1
< 0.1%
76538 1
< 0.1%

DE_solar_capacity
Real number (ℝ)

High correlation 

Distinct1464
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42373.93
Minimum37248
Maximum50508
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size684.0 KiB
2025-04-21T17:29:46.627040image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum37248
5-th percentile37531
Q138810
median40941
Q346092
95-th percentile50169
Maximum50508
Range13260
Interquartile range (IQR)7282

Descriptive statistics

Standard deviation4303.6143
Coefficient of variation (CV)0.10156279
Kurtosis-0.98120024
Mean42373.93
Median Absolute Deviation (MAD)2513
Skewness0.68489035
Sum1.8550459 × 109
Variance18521096
MonotonicityIncreasing
2025-04-21T17:29:46.928037image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37531 120
 
0.3%
38789 119
 
0.3%
49191 96
 
0.2%
41702 96
 
0.2%
50507 96
 
0.2%
37367 96
 
0.2%
37649 96
 
0.2%
39942 96
 
0.2%
37372 96
 
0.2%
39374 96
 
0.2%
Other values (1454) 42771
97.7%
ValueCountFrequency (%)
37248 24
 
0.1%
37250 72
0.2%
37252 24
 
0.1%
37253 24
 
0.1%
37256 24
 
0.1%
37258 24
 
0.1%
37260 72
0.2%
37263 24
 
0.1%
37264 24
 
0.1%
37266 24
 
0.1%
ValueCountFrequency (%)
50508 74
0.2%
50507 96
0.2%
50506 48
0.1%
50505 24
 
0.1%
50502 24
 
0.1%
50499 24
 
0.1%
50485 24
 
0.1%
50481 24
 
0.1%
50479 72
0.2%
50478 24
 
0.1%

DE_solar_generation_actual
Real number (ℝ)

High correlation  Zeros 

Distinct13490
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4303.0678
Minimum0
Maximum30028
Zeros18985
Zeros (%)43.4%
Negative0
Negative (%)0.0%
Memory size684.0 KiB
2025-04-21T17:29:47.176646image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median126
Q36818
95-th percentile19359.15
Maximum30028
Range30028
Interquartile range (IQR)6818

Descriptive statistics

Standard deviation6601.6531
Coefficient of variation (CV)1.5341736
Kurtosis1.4031231
Mean4303.0678
Median Absolute Deviation (MAD)126
Skewness1.5564744
Sum1.883797 × 108
Variance43581824
MonotonicityNot monotonic
2025-04-21T17:29:47.461662image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18985
43.4%
1 280
 
0.6%
2 181
 
0.4%
3 147
 
0.3%
4 99
 
0.2%
5 90
 
0.2%
6 64
 
0.1%
7 64
 
0.1%
8 58
 
0.1%
9 45
 
0.1%
Other values (13480) 23765
54.3%
ValueCountFrequency (%)
0 18985
43.4%
0.5 1
 
< 0.1%
1 280
 
0.6%
1.5 1
 
< 0.1%
2 181
 
0.4%
3 147
 
0.3%
4 99
 
0.2%
5 90
 
0.2%
6 64
 
0.1%
7 64
 
0.1%
ValueCountFrequency (%)
30028 1
< 0.1%
29967 1
< 0.1%
29913 1
< 0.1%
29849 1
< 0.1%
29813 1
< 0.1%
29722 1
< 0.1%
29708 1
< 0.1%
29685 1
< 0.1%
29651 1
< 0.1%
29624 1
< 0.1%

DE_wind_capacity
Real number (ℝ)

High correlation 

Distinct1367
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39967.34
Minimum27913
Maximum50452
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size684.0 KiB
2025-04-21T17:29:47.725343image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum27913
5-th percentile28882
Q133737
median39808
Q347730
95-th percentile50059
Maximum50452
Range22539
Interquartile range (IQR)13993

Descriptive statistics

Standard deviation7260.8091
Coefficient of variation (CV)0.18166856
Kurtosis-1.3866005
Mean39967.34
Median Absolute Deviation (MAD)6685
Skewness-0.02370818
Sum1.7496902 × 109
Variance52719349
MonotonicityIncreasing
2025-04-21T17:29:47.974221image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44841 264
 
0.6%
48974 192
 
0.4%
48249 168
 
0.4%
49364 168
 
0.4%
49429 144
 
0.3%
49300 144
 
0.3%
49014 144
 
0.3%
50074 144
 
0.3%
49370 144
 
0.3%
32812 144
 
0.3%
Other values (1357) 42122
96.2%
ValueCountFrequency (%)
27913 24
 
0.1%
27926 72
0.2%
27939 24
 
0.1%
27950 24
 
0.1%
27957 24
 
0.1%
27966 24
 
0.1%
27972 72
0.2%
27976 24
 
0.1%
27982 24
 
0.1%
27988 48
0.1%
ValueCountFrequency (%)
50452 2
 
< 0.1%
50434 24
 
0.1%
50427 48
0.1%
50424 96
0.2%
50409 24
 
0.1%
50403 24
 
0.1%
50399 24
 
0.1%
50370 24
 
0.1%
50361 24
 
0.1%
50345 24
 
0.1%

DE_wind_generation_actual
Real number (ℝ)

Distinct21472
Distinct (%)49.0%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean11147.869
Minimum135
Maximum45085
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size684.0 KiB
2025-04-21T17:29:48.211505image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum135
5-th percentile1494
Q14423
median8726
Q315562
95-th percentile29300.2
Maximum45085
Range44950
Interquartile range (IQR)11139

Descriptive statistics

Standard deviation8682.6073
Coefficient of variation (CV)0.77885803
Kurtosis0.77542329
Mean11147.869
Median Absolute Deviation (MAD)5041
Skewness1.1340622
Sum4.8802026 × 108
Variance75387669
MonotonicityNot monotonic
2025-04-21T17:29:48.490328image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3879 10
 
< 0.1%
3336 10
 
< 0.1%
4853 10
 
< 0.1%
3165 10
 
< 0.1%
7892 10
 
< 0.1%
4506 9
 
< 0.1%
4207 9
 
< 0.1%
4826 9
 
< 0.1%
2477 9
 
< 0.1%
2952 9
 
< 0.1%
Other values (21462) 43682
99.8%
ValueCountFrequency (%)
135 1
< 0.1%
153 2
< 0.1%
163 1
< 0.1%
165 1
< 0.1%
177 1
< 0.1%
189 1
< 0.1%
192 1
< 0.1%
203 2
< 0.1%
205 1
< 0.1%
207 1
< 0.1%
ValueCountFrequency (%)
45085 1
< 0.1%
45058 1
< 0.1%
44629 1
< 0.1%
44503 1
< 0.1%
44367 1
< 0.1%
44350 1
< 0.1%
44226 1
< 0.1%
44192 1
< 0.1%
44089 1
< 0.1%
43870 1
< 0.1%

Price (EUR/MWhe)
Real number (ℝ)

High correlation 

Distinct7314
Distinct (%)16.7%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean35.2341
Minimum-130.09
Maximum163.52
Zeros7
Zeros (%)< 0.1%
Negative646
Negative (%)1.5%
Memory size684.0 KiB
2025-04-21T17:29:48.722149image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-130.09
5-th percentile12.03
Q127.06
median34.93
Q343.82
95-th percentile58.12
Maximum163.52
Range293.61
Interquartile range (IQR)16.76

Descriptive statistics

Standard deviation15.387706
Coefficient of variation (CV)0.43672766
Kurtosis6.2495879
Mean35.2341
Median Absolute Deviation (MAD)8.27
Skewness-0.22802057
Sum1542443.2
Variance236.7815
MonotonicityNot monotonic
2025-04-21T17:29:48.972654image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22.34 105
 
0.2%
40 58
 
0.1%
30 56
 
0.1%
35 53
 
0.1%
34.94 50
 
0.1%
39.9 42
 
0.1%
42 41
 
0.1%
33 39
 
0.1%
34.9 39
 
0.1%
32 39
 
0.1%
Other values (7304) 43255
98.8%
ValueCountFrequency (%)
-130.09 1
< 0.1%
-100.06 1
< 0.1%
-83.06 1
< 0.1%
-83.04 1
< 0.1%
-83.03 1
< 0.1%
-83.02 1
< 0.1%
-83.01 1
< 0.1%
-83 2
< 0.1%
-82.06 1
< 0.1%
-81.95 1
< 0.1%
ValueCountFrequency (%)
163.52 1
< 0.1%
153.67 1
< 0.1%
151.07 1
< 0.1%
150.1 1
< 0.1%
143.09 1
< 0.1%
142.78 1
< 0.1%
138.91 1
< 0.1%
135 1
< 0.1%
133.18 1
< 0.1%
131.01 1
< 0.1%

DE_temperature
Real number (ℝ)

High correlation 

Distinct23390
Distinct (%)53.4%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean9.8602105
Minimum-12.686
Maximum35.479
Zeros1
Zeros (%)< 0.1%
Negative4663
Negative (%)10.7%
Memory size684.0 KiB
2025-04-21T17:29:49.208368image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum-12.686
5-th percentile-1.983
Q13.273
median9.249
Q316.034
95-th percentile23.631
Maximum35.479
Range48.165
Interquartile range (IQR)12.761

Descriptive statistics

Standard deviation8.1292512
Coefficient of variation (CV)0.82445006
Kurtosis-0.65315928
Mean9.8602105
Median Absolute Deviation (MAD)6.334
Skewness0.23866449
Sum431650.44
Variance66.084725
MonotonicityNot monotonic
2025-04-21T17:29:49.473326image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.99 9
 
< 0.1%
16.978 8
 
< 0.1%
12.66 8
 
< 0.1%
4.291 8
 
< 0.1%
13.112 8
 
< 0.1%
3.262 8
 
< 0.1%
9.167 7
 
< 0.1%
4.532 7
 
< 0.1%
1.202 7
 
< 0.1%
1.76 7
 
< 0.1%
Other values (23380) 43700
99.8%
ValueCountFrequency (%)
-12.686 1
< 0.1%
-12.507 1
< 0.1%
-12.353 1
< 0.1%
-11.988 1
< 0.1%
-11.619 1
< 0.1%
-11.212 1
< 0.1%
-11.146 1
< 0.1%
-11.062 1
< 0.1%
-11.027 1
< 0.1%
-10.955 1
< 0.1%
ValueCountFrequency (%)
35.479 1
< 0.1%
35.374 1
< 0.1%
35.248 1
< 0.1%
34.952 1
< 0.1%
34.713 1
< 0.1%
34.373 1
< 0.1%
34.317 1
< 0.1%
34.298 1
< 0.1%
34.176 1
< 0.1%
34.172 1
< 0.1%

DE_radiation_direct_horizontal
Real number (ℝ)

High correlation  Zeros 

Distinct25054
Distinct (%)57.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean82.819672
Minimum0
Maximum841.68104
Zeros18724
Zeros (%)42.8%
Negative0
Negative (%)0.0%
Memory size684.0 KiB
2025-04-21T17:29:49.711564image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.42644003
Q379.325396
95-th percentile475.45788
Maximum841.68104
Range841.68104
Interquartile range (IQR)79.325396

Descriptive statistics

Standard deviation159.06547
Coefficient of variation (CV)1.9206242
Kurtosis4.310132
Mean82.819672
Median Absolute Deviation (MAD)0.42644003
Skewness2.2263327
Sum3625596.8
Variance25301.823
MonotonicityNot monotonic
2025-04-21T17:29:49.974801image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18724
42.8%
7.95798668 1
 
< 0.1%
9.379364792 1
 
< 0.1%
3.822047998 1
 
< 0.1%
70.51504672 1
 
< 0.1%
18.89479469 1
 
< 0.1%
10.5469209 1
 
< 0.1%
0.2799298852 1
 
< 0.1%
0.4327949255 1
 
< 0.1%
8.877348817 1
 
< 0.1%
Other values (25044) 25044
57.2%
ValueCountFrequency (%)
0 18724
42.8%
8.171790981 × 10-71
 
< 0.1%
9.07846013 × 10-71
 
< 0.1%
9.530085836 × 10-71
 
< 0.1%
1.045591789 × 10-61
 
< 0.1%
1.06322559 × 10-61
 
< 0.1%
1.07193191 × 10-61
 
< 0.1%
1.14164887 × 10-61
 
< 0.1%
1.141725265 × 10-61
 
< 0.1%
1.173996657 × 10-61
 
< 0.1%
ValueCountFrequency (%)
841.6810378 1
< 0.1%
841.2403306 1
< 0.1%
840.6881976 1
< 0.1%
831.5056881 1
< 0.1%
829.7901916 1
< 0.1%
827.1609402 1
< 0.1%
822.3007002 1
< 0.1%
818.5285918 1
< 0.1%
814.5623326 1
< 0.1%
813.3931179 1
< 0.1%

DE_radiation_diffuse_horizontal
Real number (ℝ)

High correlation  Zeros 

Distinct25054
Distinct (%)57.2%
Missing1
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean67.120673
Minimum0
Maximum392.08953
Zeros18724
Zeros (%)42.8%
Negative0
Negative (%)0.0%
Memory size684.0 KiB
2025-04-21T17:29:50.227601image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.3509196
Q3119.66999
95-th percentile254.93552
Maximum392.08953
Range392.08953
Interquartile range (IQR)119.66999

Descriptive statistics

Standard deviation89.201568
Coefficient of variation (CV)1.3289731
Kurtosis0.74047776
Mean67.120673
Median Absolute Deviation (MAD)6.3509196
Skewness1.2607732
Sum2938341.7
Variance7956.9197
MonotonicityNot monotonic
2025-04-21T17:29:50.608768image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 18724
42.8%
100.6625133 1
 
< 0.1%
108.5543352 1
 
< 0.1%
45.275952 1
 
< 0.1%
81.73645328 1
 
< 0.1%
51.04470531 1
 
< 0.1%
112.3496791 1
 
< 0.1%
2.273970115 1
 
< 0.1%
6.768005075 1
 
< 0.1%
51.94635118 1
 
< 0.1%
Other values (25044) 25044
57.2%
ValueCountFrequency (%)
0 18724
42.8%
8.675676469 × 10-51
 
< 0.1%
8.78007015 × 10-51
 
< 0.1%
8.7845987 × 10-51
 
< 0.1%
8.795196726 × 10-51
 
< 0.1%
9.074600853 × 10-51
 
< 0.1%
9.07794107 × 10-51
 
< 0.1%
9.173733963 × 10-51
 
< 0.1%
9.225912742 × 10-51
 
< 0.1%
9.230272995 × 10-51
 
< 0.1%
ValueCountFrequency (%)
392.0895324 1
< 0.1%
390.2950449 1
< 0.1%
389.785004 1
< 0.1%
389.722721 1
< 0.1%
387.7550278 1
< 0.1%
385.454346 1
< 0.1%
384.7493436 1
< 0.1%
384.68629 1
< 0.1%
384.6193791 1
< 0.1%
384.2284195 1
< 0.1%

Gas_Price
Real number (ℝ)

Distinct220
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7684353
Minimum1.49
Maximum6.24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size684.0 KiB
2025-04-21T17:29:50.956528image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1.49
5-th percentile1.91
Q12.54
median2.79
Q32.98
95-th percentile3.56
Maximum6.24
Range4.75
Interquartile range (IQR)0.44

Descriptive statistics

Standard deviation0.50564694
Coefficient of variation (CV)0.1826472
Kurtosis4.5642933
Mean2.7684353
Median Absolute Deviation (MAD)0.21
Skewness0.92941831
Sum121196.56
Variance0.25567883
MonotonicityNot monotonic
2025-04-21T17:29:51.210878image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.88 1200
 
2.7%
2.75 1104
 
2.5%
2.96 912
 
2.1%
2.89 816
 
1.9%
2.76 768
 
1.8%
2.7 720
 
1.6%
2.95 672
 
1.5%
2.98 672
 
1.5%
2.78 672
 
1.5%
2.91 672
 
1.5%
Other values (210) 35570
81.3%
ValueCountFrequency (%)
1.49 72
0.2%
1.56 24
 
0.1%
1.57 24
 
0.1%
1.59 24
 
0.1%
1.6 48
 
0.1%
1.61 24
 
0.1%
1.62 24
 
0.1%
1.63 120
0.3%
1.66 24
 
0.1%
1.68 24
 
0.1%
ValueCountFrequency (%)
6.24 48
 
0.1%
5.46 24
 
0.1%
4.7 120
0.3%
4.69 48
 
0.1%
4.65 144
0.3%
4.61 72
0.2%
4.54 24
 
0.1%
4.53 48
 
0.1%
4.51 72
0.2%
4.5 48
 
0.1%

Oil_Price
Real number (ℝ)

High correlation 

Distinct1064
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.09679
Minimum26.01
Maximum86.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size684.0 KiB
2025-04-21T17:29:51.475441image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum26.01
5-th percentile37.22
Q148.1
median57.02
Q365.02
95-th percentile75.89
Maximum86.07
Range60.06
Interquartile range (IQR)16.92

Descriptive statistics

Standard deviation11.529101
Coefficient of variation (CV)0.20192206
Kurtosis-0.480539
Mean57.09679
Median Absolute Deviation (MAD)8.53
Skewness-0.039511655
Sum2499583.3
Variance132.92018
MonotonicityNot monotonic
2025-04-21T17:29:51.706104image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54.8 168
 
0.4%
46.69 168
 
0.4%
55.73 144
 
0.3%
70.71 144
 
0.3%
64.68 144
 
0.3%
69.02 144
 
0.3%
61.04 144
 
0.3%
47.28 144
 
0.3%
51.93 144
 
0.3%
38.33 120
 
0.3%
Other values (1054) 42314
96.7%
ValueCountFrequency (%)
26.01 24
 
0.1%
27.36 48
0.1%
27.59 24
 
0.1%
28.58 24
 
0.1%
28.8 72
0.2%
28.82 24
 
0.1%
28.84 24
 
0.1%
29.14 24
 
0.1%
29.64 24
 
0.1%
29.82 24
 
0.1%
ValueCountFrequency (%)
86.07 24
 
0.1%
85.63 24
 
0.1%
85.45 24
 
0.1%
85.16 24
 
0.1%
85.12 72
0.2%
84.94 24
 
0.1%
84.22 24
 
0.1%
83.82 24
 
0.1%
82.72 72
0.2%
82.21 24
 
0.1%

Interactions

2025-04-21T17:29:41.845633image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:19.850107image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:22.351553image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:24.747317image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:26.861766image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:28.996124image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:31.196414image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:33.278995image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:35.362737image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:37.544662image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:39.795948image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:42.029409image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:20.126552image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:22.539558image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:24.928594image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:27.028881image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:29.178272image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:31.394795image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:33.462712image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:35.545290image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:37.745804image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:39.978368image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:42.212415image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:20.529920image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:22.750043image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:25.138940image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:27.311104image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:29.389013image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:31.578763image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:33.645205image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:35.745260image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:37.947825image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:40.164314image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:42.428866image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:20.774772image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:23.039560image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:25.345888image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:27.500018image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:29.563138image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:31.779279image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:33.840091image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:35.928936image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:38.146809image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:40.366445image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:42.611011image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:21.028629image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:23.278698image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:25.537966image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:27.679652image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:29.889258image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:31.961509image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:34.029054image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:36.097084image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:38.364452image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:40.526005image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:42.779012image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:21.197627image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:23.481478image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:25.713187image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:27.862261image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:30.064466image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:32.139791image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:34.268333image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:36.278688image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:38.545433image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:40.698530image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:42.947915image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:21.413485image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:23.681035image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:25.896630image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:28.045016image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:30.248064image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:32.331399image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:34.462673image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:36.463136image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:38.763587image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:40.866911image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:43.111475image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:21.598519image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:23.867097image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:26.080572image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:28.213844image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:30.428470image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:32.495258image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:34.633220image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:36.792959image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:38.982131image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:41.042636image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:43.294903image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:21.762460image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:24.045931image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:26.263228image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:28.395530image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:30.596390image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:32.711276image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:34.793027image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:36.963743image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:39.195991image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:41.240368image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:43.498159image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:21.982953image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:24.263791image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:26.499222image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:28.612422image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:30.797614image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:32.912889image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:35.011498image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:37.164177image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:39.430077image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:41.512891image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:43.669462image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:22.163620image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:24.560599image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:26.662255image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:28.809800image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:30.993100image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:33.094812image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:35.184176image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:37.364791image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:39.614198image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-04-21T17:29:41.677825image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Correlations

2025-04-21T17:29:51.876203image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
DE_load_actual_entsoe_transparencyDE_radiation_diffuse_horizontalDE_radiation_direct_horizontalDE_solar_capacityDE_solar_generation_actualDE_temperatureDE_wind_capacityDE_wind_generation_actualGas_PriceOil_PricePrice (EUR/MWhe)
DE_load_actual_entsoe_transparency1.0000.4570.4430.0440.454-0.0540.0430.0710.0600.0230.545
DE_radiation_diffuse_horizontal0.4571.0000.941-0.0140.9510.470-0.014-0.150-0.0310.0230.107
DE_radiation_direct_horizontal0.4430.9411.000-0.0070.9850.507-0.007-0.206-0.0280.0460.102
DE_solar_capacity0.044-0.014-0.0071.0000.0100.0801.0000.2270.0760.6440.336
DE_solar_generation_actual0.4540.9510.9850.0101.0000.5020.010-0.183-0.0340.0490.093
DE_temperature-0.0540.4700.5070.0800.5021.0000.080-0.243-0.0370.083-0.037
DE_wind_capacity0.043-0.014-0.0071.0000.0100.0801.0000.2270.0760.6440.336
DE_wind_generation_actual0.071-0.150-0.2060.227-0.183-0.2430.2271.0000.0240.122-0.274
Gas_Price0.060-0.031-0.0280.076-0.034-0.0370.0760.0241.0000.2550.231
Oil_Price0.0230.0230.0460.6440.0490.0830.6440.1220.2551.0000.359
Price (EUR/MWhe)0.5450.1070.1020.3360.093-0.0370.336-0.2740.2310.3591.000

Missing values

2025-04-21T17:29:43.908190image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-21T17:29:44.341625image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-04-21T17:29:44.711440image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

cet_cest_timestampDE_load_actual_entsoe_transparencyDE_solar_capacityDE_solar_generation_actualDE_wind_capacityDE_wind_generation_actualPrice (EUR/MWhe)DE_temperatureDE_radiation_direct_horizontalDE_radiation_diffuse_horizontalGas_PriceOil_Price
utc_timestamp
2014-12-31 23:00:002015-01-01T00:00:00+0100NaN37248.00.027913.0NaNNaNNaNNaNNaN3.1455.38
2015-01-01 00:00:002015-01-01T01:00:00+010041151.037248.00.027913.08852.022.34-0.9810.0000000.0000003.1455.38
2015-01-01 01:00:002015-01-01T02:00:00+010040135.037248.00.027913.09054.022.34-1.0350.0000000.0000003.1455.38
2015-01-01 02:00:002015-01-01T03:00:00+010039106.037248.00.027913.09070.022.34-1.1090.0000000.0000003.1455.38
2015-01-01 03:00:002015-01-01T04:00:00+010038765.037248.00.027913.09163.022.34-1.1660.0000000.0000003.1455.38
2015-01-01 04:00:002015-01-01T05:00:00+010038941.037248.00.027913.09231.022.34-1.2260.0000000.0000003.1455.38
2015-01-01 05:00:002015-01-01T06:00:00+010039045.037248.00.027913.09689.022.34-1.3050.0000000.0000003.1455.38
2015-01-01 06:00:002015-01-01T07:00:00+010040206.037248.00.027913.010331.022.34-1.4780.0000000.0000003.1455.38
2015-01-01 07:00:002015-01-01T08:00:00+010041133.037248.071.027913.010208.022.34-1.6920.4327956.7680053.1455.38
2015-01-01 08:00:002015-01-01T09:00:00+010042963.037248.0773.027913.010029.022.34-1.0468.87734951.9463513.1455.38
cet_cest_timestampDE_load_actual_entsoe_transparencyDE_solar_capacityDE_solar_generation_actualDE_wind_capacityDE_wind_generation_actualPrice (EUR/MWhe)DE_temperatureDE_radiation_direct_horizontalDE_radiation_diffuse_horizontalGas_PriceOil_Price
utc_timestamp
2019-12-29 15:00:002019-12-29T16:00:00+010049244.050508.0105.050434.014808.034.47-0.9290.279932.273971.7568.91
2019-12-29 16:00:002019-12-29T17:00:00+010052332.050508.00.050434.016721.039.81-0.9820.000000.000001.7568.91
2019-12-29 17:00:002019-12-29T18:00:00+010052958.050508.00.050434.018357.040.47-0.8730.000000.000001.7568.91
2019-12-29 18:00:002019-12-29T19:00:00+010051943.050508.00.050434.019397.038.96-0.8800.000000.000001.7568.91
2019-12-29 19:00:002019-12-29T20:00:00+010049806.050508.00.050434.019506.035.35-0.9590.000000.000001.7568.91
2019-12-29 20:00:002019-12-29T21:00:00+010048362.050508.00.050434.020610.030.47-1.0150.000000.000001.7568.91
2019-12-29 21:00:002019-12-29T22:00:00+010047950.050508.00.050434.021107.028.64-1.0380.000000.000001.7568.91
2019-12-29 22:00:002019-12-29T23:00:00+010045146.050508.00.050434.021740.023.06-1.0790.000000.000001.7568.91
2019-12-29 23:00:002019-12-30T00:00:00+010043026.050508.00.050452.022553.013.54-1.1380.000000.000001.7568.91
2019-12-30 00:00:002019-12-30T01:00:00+010041138.050508.00.050452.022793.011.42-1.1620.000000.000002.0668.30